Lack of validation of genetic variants associated with anti-tumor necrosis factor therapy response in rheumatoid arthritis: a genome-wide association study replication and meta-analysis

Ana Márquez, Aida Ferreiro-Iglesias, Cristina L Dávila-Fajardo, Ariana Montes, Dora Pascual-Salcedo, Eva Perez-Pampin, Manuel J Moreno-Ramos, Rosa García-Portales, Federico Navarro, Virginia Moreira, César Magro, Rafael Caliz, Miguel Angel Ferrer, Juan José Alegre-Sancho, Beatriz Joven, Patricia Carreira, Alejandro Balsa, Yiannis Vasilopoulos, Theologia Sarafidou, José Cabeza-Barrera, Javier Narvaez, Enrique Raya, Juan D Cañete, Antonio Fernández-Nebro, María del Carmen Ordóñez, Arturo R de la Serna, Berta Magallares, Juan J Gomez-Reino, Antonio González, Javier Martín, Ana Márquez, Aida Ferreiro-Iglesias, Cristina L Dávila-Fajardo, Ariana Montes, Dora Pascual-Salcedo, Eva Perez-Pampin, Manuel J Moreno-Ramos, Rosa García-Portales, Federico Navarro, Virginia Moreira, César Magro, Rafael Caliz, Miguel Angel Ferrer, Juan José Alegre-Sancho, Beatriz Joven, Patricia Carreira, Alejandro Balsa, Yiannis Vasilopoulos, Theologia Sarafidou, José Cabeza-Barrera, Javier Narvaez, Enrique Raya, Juan D Cañete, Antonio Fernández-Nebro, María del Carmen Ordóñez, Arturo R de la Serna, Berta Magallares, Juan J Gomez-Reino, Antonio González, Javier Martín

Abstract

Introduction: In this study, our aim was to elucidate the role of four polymorphisms identified in a prior large genome-wide association study (GWAS) in which the investigators analyzed the responses of patients with rheumatoid arthritis (RA) to treatment with tumor necrosis factor inhibitors (TNFi). The authors of that study reported that the four genetic variants were significantly associated. However, none of the associations reached GWAS significance, and two subsequent studies failed to replicate these associations.

Methods: The four polymorphisms (rs12081765, rs1532269, rs17301249 and rs7305646) were genotyped in a total of 634 TNFi-treated RA patients of Spanish Caucasian origin. Four outcomes were evaluated: changes in the Disease Activity Score in 28 joints (DAS28) after 6 and 12 months of treatment and classification according to the European League Against Rheumatism (EULAR) response criteria at the same time points. Association with DAS28 changes was assessed by linear regression using an additive genetic model. Contingency tables of genotype and allele frequencies between EULAR responder and nonresponder patients were compared. In addition, we combined our data with those of previously reported studies in a meta-analysis including 2,998 RA patients.

Results: None of the four genetic variants showed an association with response to TNFi in any of the four outcomes analyzed in our Spanish patients. In addition, only rs1532269 yielded a suggestive association (P = 0.0033) with the response to TNFi when available data from previous studies were combined in the meta-analysis.

Conclusion: Our data suggest that the rs12081765, rs1532269, rs17301249 and rs7305646 genetic variants do not have a role as genetic predictors of TNFi treatment outcomes.

References

    1. Scott DL, Wolfe F, Huizinga TW. Rheumatoid arthritis. Lancet. 2010;376:1094–1108. doi: 10.1016/S0140-6736(10)60826-4.
    1. Breedveld FC, Weisman MH, Kavanaugh AF, Cohen SB, Pavelka K, van Vollenhoven R, Sharp J, Perez JL, Spencer-Green GT. The PREMIER study: a multicenter, randomized, double-blind clinical trial of combination therapy with adalimumab plus methotrexate versus methotrexate alone or adalimumab alone in patients with early, aggressive rheumatoid arthritis who had not had previous methotrexate treatment. Arthritis Rheum. 2006;54:26–37. doi: 10.1002/art.21519.
    1. Emery P, Breedveld FC, Hall S, Durez P, Chang DJ, Robertson D, Singh A, Pedersen RD, Koenig AS, Freundlich B. Comparison of methotrexate monotherapy with a combination of methotrexate and etanercept in active, early, moderate to severe rheumatoid arthritis (COMET): a randomised, double-blind, parallel treatment trial. Lancet. 2008;372:375–382. doi: 10.1016/S0140-6736(08)61000-4.
    1. Smolen JS, Van Der Heijde DM, St Clair EW, Emery P, Bathon JM, Keystone E, Maini RN, Kalden JR, Schiff M, Baker D, Han C, Han J, Bala M. Active-Controlled Study of Patients Receiving Infliximab for the Treatment of Rheumatoid Arthritis of Early Onset (ASPIRE) Study Group. Predictors of joint damage in patients with early rheumatoid arthritis treated with high-dose methotrexate with or without concomitant infliximab: results from the ASPIRE trial. Arthritis Rheum. 2006;54:702–710. doi: 10.1002/art.21678.
    1. Gibbons LJ, Hyrich KL. Biologic therapy for rheumatoid arthritis: clinical efficacy and predictors of response. BioDrugs. 2009;23:111–124. doi: 10.2165/00063030-200923020-00004.
    1. Hetland ML, Christensen IJ, Tarp U, Dreyer L, Hansen A, Hansen IT, Kollerup G, Linde L, Lindegaard HM, Poulsen UE, Schlemmer A, Jensen DV, Jensen S, Hostenkamp G, Østergaard M. All Departments of Rheumatology in Denmark. Direct comparison of treatment responses, remission rates, and drug adherence in patients with rheumatoid arthritis treated with adalimumab, etanercept, or infliximab: results from eight years of surveillance of clinical practice in the nationwide Danish DANBIO registry. Arthritis Rheum. 2010;62:22–32. doi: 10.1002/art.27227.
    1. Liu C, Batliwalla F, Li W, Lee A, Roubenoff R, Beckman E, Khalili H, Damle A, Kern M, Furie R, Dupuis J, Plenge RM, Coenen MJ, Behrens TW, Carulli JP, Gregersen PK. Genome-wide association scan identifies candidate polymorphisms associated with differential response to anti-TNF treatment in rheumatoid arthritis. Mol Med. 2008;14:575–581.
    1. Plant D, Bowes J, Potter C, Hyrich KL, Morgan AW, Wilson AG, Isaacs JD, Barton A. Genome-wide association study of genetic predictors of anti-tumor necrosis factor treatment efficacy in rheumatoid arthritis identifies associations with polymorphisms at seven loci. Arthritis Rheum. 2011;63:645–653. doi: 10.1002/art.30130.
    1. Krintel SB, Palermo G, Johansen JS, Germer S, Essioux L, Benayed R, Badi L, Østergaard M, Hetland ML. Investigation of single nucleotide polymorphisms and biological pathways associated with response to TNFα inhibitors in patients with rheumatoid arthritis. Pharmacogenet Genomics. 2012;22:577–589. doi: 10.1097/FPC.0b013e3283544043.
    1. Umiċeviċ Mirkov M, Cui J, Vermeulen SH, Stahl EA, Toonen EJ, Makkinje RR, Lee AT, Huizinga TW, Allaart R, Barton A, Mariette X, Miceli CR, Criswell LA, Tak PP, de Vries N, Saevarsdottir S, Padyukov L, Bridges SL, van Schaardenburg DJ, Jansen TL, Dutmer EA, van de Laar MA, Barrera P, Radstake TR, van Riel PL, Scheffer H, Franke B, Brunner HG, Plenge RM, Gregersen PK. et al.Genome-wide association analysis of anti-TNF drug response in patients with rheumatoid arthritis. Ann Rheum Dis. 2013;72:1375–1381. doi: 10.1136/annrheumdis-2012-202405.
    1. Cui J, Stahl EA, Saevarsdottir S, Miceli C, Diogo D, Trynka G, Raj T, Mirkov MU, Canhao H, Ikari K, Terao C, Okada Y, Wedrén S, Askling J, Yamanaka H, Momohara S, Taniguchi A, Ohmura K, Matsuda F, Mimori T, Gupta N, Kuchroo M, Morgan AW, Isaacs JD, Wilson AG, Hyrich KL, Herenius M, Doorenspleet ME, Tak PP, Crusius JB. et al.Genome-wide association study and gene expression analysis identifies CD84 as a predictor of response to etanercept therapy in rheumatoid arthritis. PLoS Genet. 2013;9:e1003394. doi: 10.1371/journal.pgen.1003394.
    1. Acosta-Colman I, Palau N, Tornero J, Fernández-Nebro A, Blanco F, González-Alvaro I, Cañete JD, Maymó J, Ballina J, Fernández-Gutiérrez B, Olivé A, Corominas H, Erra A, Canela-Xandri O, Alonso A, López Lasanta M, Tortosa R, Julià A, Marsal S. GWAS replication study confirms the association of PDE3A-SLCO1C1 with anti-TNF therapy response in rheumatoid arthritis. Pharmacogenomics. 2013;14:727–734. doi: 10.2217/pgs.13.60.
    1. Cui J, Saevarsdottir S, Thomson B, Padyukov L, van der Helm-van Mil AH, Nititham J, Hughes LB, de Vries N, Raychaudhuri S, Alfredsson L, Askling J, Wedrén S, Ding B, Guiducci C, Wolbink GJ, Crusius JB, van der Horst-Bruinsma IE, Herenius M, Weinblatt ME, Shadick NA, Worthington J, Batliwalla F, Kern M, Morgan AW, Wilson AG, Isaacs JD, Hyrich K, Seldin MF, Moreland LW, Behrens TW. et al.Rheumatoid arthritis risk allele PTPRC is also associated with response to anti-tumor necrosis factor α therapy. Arthritis Rheum. 2010;62:1849–1861.
    1. Plant D, Prajapati R, Hyrich KL, Morgan AW, Wilson AG, Isaacs JD, Barton A. Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate. Replication of association of the PTPRC gene with response to anti-tumor necrosis factor therapy in a large UK cohort. Arthritis Rheum. 2012;64:665–670. doi: 10.1002/art.33381.
    1. Arnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF, Cooper NS, Healey LA, Kaplan SR, Liang MH, Luthra HS, Medsger TA Jr, Mitchell DM, Neustadt DH, Pinals RS, Schaller JG, Sharp JT, Wilder RL, Hunder GG. The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum. 1988;31:315–324. doi: 10.1002/art.1780310302.
    1. van Gestel AM, Prevoo ML, Van’ t Hof MA, van Rijswijk MH, van de Putte LB, van Riel PL. Development and validation of the European League against Rheumatism response criteria for rheumatoid arthritis, comparison with the preliminary American College of Rheumatology and the World Health Organization/International League against Rheumatism criteria. Arthritis Rheum. 1996;39:34–40. doi: 10.1002/art.1780390105.
    1. Gauderman WJ, Morrison JM. QUANTO 1.1: A computer program for power and sample size calculations for genetic-epidemiology studies (2006) [ ]
    1. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–575. doi: 10.1086/519795.
    1. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B. 1995;57:289–300.
    1. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557–560. doi: 10.1136/bmj.327.7414.557.
    1. Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN. Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet. 2003;33:177–182. doi: 10.1038/ng1071.

Source: PubMed

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